Fusion of disparate spectra for chemical identification

摘要

Currently there is no systematic framework for characterizing fused, multisensory systems, and therefore the comparison of multiple independent systems is difficult without extensive field-testing. Development of a framework would allow for theoretical comparisons and enable more rapid prototyping of fused sensor systems, guidance for design from existing sensor components, and more effective engineering of new sensors optimized for use in fused sensor systems. Recent research at NRL has focused on characterizing Fourier transform infrared spectroscopy (FTIR) and mass spectrometry data for fused, multisensor applications to enhance chemical detection and discrimination in the presence of complex interfering backgrounds. An information theoretic approach has been used to elucidate the information content available from spectral data, quantify the ability of these sensing techniques to distinguish chemicals, and determine their susceptibility to noise and resolution limitations. The approach has also been applied to feature extraction and data fusion techniques on these data. Results characterizing the effectiveness of a fused multisensor system combining FTIR and mass spectrometry are presented.